Background: One of the effective factors in successful implementation of health information technology, especially electronic medical record, is investigation of adoption and its use by users. Therefore, the aim of this study was to investigate factors affecting adoption and use of electronic medical record in Shiraz teaching hospitals from the perceptive of top and middle managers.

Background: Machine learning is a type of artificial intelligence which aims to improve machine with the ability of extracting knowledge from the environment. Glioblastoma multiforme (GBM) is one of the most common and aggressive primary malignant brain tumors in adults. Due to a low rate of survival in patients with these tumors, machine learning can help physicians for better decision-making. The aim of this paper is to develop a machine learning model for predicting the survival rate of patients with GBM based on clinical features and magnetic resonance imaging (MRI). Materials and Methods: The present investigation is an observational study conducted to predict the survival rate in patients with GBM in 12 months. Fifty-five patients who were registered in five Iranian Hospitals (Tehran) during 2012–2014 were selected in this study. Results: This study used Cox and C5.0 decision tree models based on clinical features and combined them with MRI. Accuracy, sensitivity, and specification parameters used to evaluate the models. The result of Cox and C5.0 for clinical feature was <32.73%, 22.5%, 45.83%>, <72.73%, 67.74%, 79.19%>, respectively; also, the result of Cox and C5.0 for both features was <60%, 48.58%, 75%>, <90.91%, 96.77%, 88.33%>, respectively. Conclusion: Using C5.0 decision tree model in both survival models including clinical features, both the imaging features and the clinical features as the covariates, shows additional predictive values and better results. The tumor width and Karnofsky performance status scores were determined as the most important parameters in the survival prediction of these types of patients.

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BackgroundHospital websites are considered as an appropriate system for exchanging information and establishing communication between patients, hospitals, and medical staff. Website character, website contact interactivity, shopping convenience, as well as care and service are the factors that the present study investigated as far as the patient relationship management is concerned.MethodsThis descriptive-analytical study was conducted on 206 patients visiting Shahid Faghihi and Ali Asghar Hospitals in Shiraz, which were capable of offering electronic services. The data collection tool was a researcher-made questionnaire based on the Mekkamol model and other similar studies, as well as investigations into the websites of the world’s top hospitals. The questionnaire’s validity was approved by a committee of experts and its reliability was approved based on a 54-patient sample with a Cronbach’s alpha of 0.94. The data were analyzed using the Structural Equation Modeling (SEM) with partial least squares (PLS) approach and by utilizing SPSS and Smart-PLS V2 software programs.ResultsThe results showed that there are significant relationships between “website character” and “website contact interactivity” (p=0.00), between “shopping convenience” and “website contact interactivity” (p=0.00), and between “website contact interactivity” and “care and service” (p=0.00).ConclusionWebsite design with such characteristics as website simplicity, shopping convenience, authenticity of information, and provision of such services as admission, scheduling appointments, and electronic payment of bills will result in interaction and communication between patients and hospital websites. This will, for its turn, pave the way for attracting more patients.

Introduction: The evaluation of information systems by health care professionals is one of the key factors for improving the acceptability and usability of systems. Picture Archiving and Communication System (PACS) is the support for more accurate diagnosis in the medical field. Therefore, the present study aimed to determine the factors affecting the continuance of this system in teaching hospitals of Shiraz University of Medical Sciences.Materials and Methods: This is a descriptive-analytic cross-sectional study conducted in 2014. The sample consisted of 200 PACS users (general practitioners, residents, specialists and radiologists) in Faghihi and Nemazee hospitals of Shiraz. They were selected by stratified random sampling. Data were collected using a researcher-made questionnaire. To confirm the reliability of the questionnaire, the Cronbach's alpha coefficient (84%) was used and 5 experts from health information management were used to confirm the validity of the questionnaire. The results of the present study were analyzed using descriptive statistics (frequency, mean and standard deviation) and inferential statistics (Independent t-test, ANOVA, Pearson correlation coefficient and regression tests) using SPSS 22 software.Results: The study showed that in selected hospitals according to the model, the highest correlation was found between the relationship between expectation confirmation of and satisfaction (r=0.682; R2=0.465) and the least correlation was related to the relationship between the expectation confirmation and the compatibility (r=0.347; R2=0.120). Also, there was a significant relationship between the level of education of users and the continuance intention to use the PACS system (P-value = 0.008). Radiologists have the highest tendency to continue using the PACS system and the least-favored were specialists.Conclusion: The results of the research indicate that for continued use of information systems by users and increase their satisfaction and the success of systems, consideration of users' expectations, requirements and technical requirements of systems to fit the system with the tasks of users before implementing information systems is necessary and inevitable.